Variable Reduction for Water Quality Investigation using VARCLUS Technique. A Case Study of Mosul Dam Lake, Northern Iraq

Water quality data parameters consist of a large data set. Such a large amount of data incurs great effort in processing and conducting visualization techniques to facilitate the analysis and building of the necessary views for decision makers. The current study included a set of steps to data reduction for 34 parameters during two seasons, at different sites and depths for Mosul Dam Lake, Northern Iraq by using VARCLUS technique. VARCLUS showed that there were seven main clusters during winter with 77% of the total variation in the dataset. Depending on Rratio results indicating that there are 12 parameters could be used to monitoring the water quality and F, SO4 and Li are appears to be more important parameters than among them to predict overall the water quality of the lake for this season. During summer eight main clusters with 79% of the total variation displayed result of summer season. B, Na and S were more significant parameters depending on Rratio among 11 parameters for this season. Each of Li, Ni, S, and total inorganic carbon are dominate parameters during measurement periods. This technique for water quality assessment could be using to reduce by about 64% of water quality data and can support decision-makers by providing an effective and secure tool for managing and monitoring the reservoir.